Method for detecting flow abnormity of wireless sensor network based on GM model

Abstract

The invention discloses a method for detecting the flow abnormity of a wireless sensor network based on a GM model. The method employs the GM (1, 1) model, is small in amount of used historical data, is quick in building speed of a model, is accurate in prediction value, and is very suitable for the condition that the node energy and calculation capability of the wireless sensor network are limited. enabling a historical modeling data quantity to be fixed through employing a sliding window in a proper size, thereby guaranteeing the quickness of modeling and also guaranteeing the latest effectiveness of historical data; optimizing albinism differential equation solving initial conditions of the GM (1, 1) model, and enabling the prediction value to be more accurate; generating a flow prediction value, finally used for abnormal judgment, at the next moment through the exponential weighting mean of the former L predication values, thereby introducing certain inertia to the prediction of flow. When an abnormal flow happens, a normal flow prediction model cannot be changed easily, but a normal flow prediction value can be obtained better, and the flow abnormality can be detected more easily.

Description

technical field [0001] The invention belongs to the technical field of network security, and in particular relates to a GM model-based abnormality detection method for wireless sensor network traffic. Background technique [0002] With the development of communication and computer technology, the network has become an important factor in the development of today's world. As one of the important network technologies, wireless sensor networks (Wireless Sensor Networks) are widely used in national defense, military and national security due to their advantages of high robustness, high accuracy, high flexibility and strong intelligence. , environmental monitoring, traffic management, medical and health, manufacturing, anti-terrorism and disaster relief, and other fields are also the main way for the Internet of Things to obtain information. The wireless sensor network can sense and collect information of various environments or monitoring objects through the real-time monitorin...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the defect of relatively large algorithm complexity that is common in current wireless sensor network traffic anomaly detection methods. In order to achieve more efficient real-time traffic anomaly detection under the premise of ensuring detection accuracy, a new method is proposed. A GM model-based traffic anomaly detection method for wireless sensor networks

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